摘要
为了解决负载变化导致的机器人控制性能降低的问题,本文在分析负载动力学参数对各关节力矩的影响的基础上,提出了一种仅驱动机器人的第3、4、5、6轴运行激励轨迹的辨识方法.首先,基于最小惯性参数集线性化工业机器人动力学模型;其次,在分析负载参数对各关节力矩的影响的基础上,选取相应的运动关节轴,设计适用于负载辨识的有限项傅里叶级数的优化激励轨迹;然后,在空载和带3种不用负载情况下运行激励轨迹,采集关节角度和关节力矩数据,并将数据通过低通滤波器处理;最后,基于动力学线性模型使用加权最小二乘法辨识负载动力学参数.机器人运行验证轨迹,通过计算负载力矩计算值和测量值的差的均方根(RMS)来评价负载辨识结果.同时将该方法与CAD(computer aided design)方法对比,结果显示前者最多可以将后者RMS值降为原来的16%,且该方法对不同负载辨识结果稳定有效.该方法避免了驱动所有关节轴运动的方式,减小了机器人耦合带来的误差,同时缩短了激励轨迹参数优化时间,有效提高负载动力学参数的辨识效率和效果.
In order to solve the problem of control performance degradation of the robot due to the payload changes,an identification method by driving only the 3 rd,4 th,5 th and 6 th axes of the robot along the excitation trajectory is proposed,based on the analysis of the effect of payload dynamics parameters on the torque of each joint.Firstly,the robot dynamics model is linearized based on the minimum inertia parameter set.Secondly,the optimal excitation trajectory is designed with the finite Fourier series for payload identification based on the analysis of the effect of the payload parameters on each joint torque,after selecting corresponding joint axis.Then the data of joint angle and joint torque are collected respectively while the excitation trajectory is run in conditions of no payload and other three different payloads,before they are processed by the low-pass filter.Finally,the weighted least square method is used to identify the payload dynamics parameters based on dynamic linear model.After the robot runs the verification trajectory,the payload identification result is evaluated by calculating the root mean square(RMS)of the difference between the calculated payload torque and the measured payload torque.At the same time,this method is compared with CAD(computer aided design)method.Results show that the former method can reduce the RMS value of the latter up to 16%,and that it is stable and effective under different payloads.Using this method,the way to drive all the joint axes is avoided,and thus not only the error caused by the coupling of the robot,but also the optimization time of the excitation trajectory are reduced.In conclusion,it effectively improves the efficiency and the effect of the payload dynamics parameters identification.
作者
陈友东
胡澜晓
CHEN Youdong;HU Lanxiao(School of Mechanical Engineering and Automation,Beihang University,Beijing 100191,China)
出处
《机器人》
EI
CSCD
北大核心
2020年第3期325-335,共11页
Robot
关键词
负载
工业机器人
动力学参数
参数辨识
激励轨迹
payload
industrial robot
dynamic parameter
parameter identification
excitation trajectory
